Plant state monitoring method, plant state monitoring computer program, and plant state monitoring apparatus

ABSTRACT

Provided is a plant state monitoring method which monitors an operation state of a plant by using the Mahalanobis distance based on the plant state amount. The method creates a first unit space as a set of data used to be a reference when judging whether the plant operation state during a start operation period is normal according to the state amount in the plant start operation period. The method also creates a second unit space as a set of data used to be a reference when judging whether the plant operation state during a load operation period is normal according to the state amount in the plant load operation period.

RELATED APPLICATIONS

The present application is a continuation application of U.S.application Ser. No. 12/679,619 which is a national phase ofPCT/JP2009/053747, filed on Feb. 27, 2009, which, in turn, claimspriority from Japanese Patent Application No. 2008-046696, filed Feb.27, 2008, and Japanese Patent Application No. 2008-308802, filed Dec. 3,2008. The contents of all of the above-listed prior applications areincorporated herein by reference in their entirety.

TECHNICAL FIELD

The present invention relates to a plant state monitoring method ofdetermining whether or not a plant is normally operated, a computerprogram used to monitor the state of a plant, and a plant statemonitoring apparatus.

BACKGROUND ART

In various kinds of plants, such as gas turbine power generation plants,nuclear power generation plants, and chemical plants, the quantity ofstate of the plant, such as temperature or pressure, is acquired fromthe plant in order to monitor whether or not the plant is normallyoperated. In monitoring the plant, it is necessary to monitor aplurality of state quantities and the tendency of the state quantities,and a skilled technique capable of determining whether or not the plantis normally operated is needed. The following Patent Citation 1discloses a technique in which a plurality of reference spaces (referredto as unit spaces) is prepared for each season in a year and is used tocorrespond to a season variation, thereby monitoring the operation stateof a refrigeration cycle apparatus based on the Mahalanobis distance.When this technique is applied to monitor the plant, it is possible torelatively easily monitor a plurality of state quantities.

[Patent Citation 1]

-   Japanese Unexamined Patent Application, First Publication No.    2005-207644

DISCLOSURE OF INVENTION Technical Problem

However, in the technique disclosed in the above Patent Citation 1, itis possible to determine whether there is an abnormality when a ratedload is applied based on the relationship between the Mahalanobisdistance and the unit space that is created from the quantity of stateacquired when the rated load is applied. However, since the operationstate during a startup is different from that when the rated load isapplied, a normal state is likely to be erroneously determined to be anabnormal state.

The performance of the plant is likely to be reduced due to, forexample, the deterioration of apparatuses over time. In some cases, adecrease in performance over time is assumed in advance and a certaindegree of decreased performance is regarded as a normal state. In thisstate, the plant is continuously operated. In the technique disclosed inthe above Patent Citation 1, different unit spaces are used in a year.During the period for which the same unit space is used, thedeterioration of the performance over time is likely to be determined asabnormal.

The present invention has been made in order to solve theabove-mentioned problems, and an object of the present invention is toprovide a plant state monitoring method, a plant state monitoringcomputer program, and a plant state monitoring apparatus capable ofaccurately determining whether the state of a plant is normal orabnormal when a start operation is performed under operation conditionsdifferent from those when a rated load is applied, and when theperformance of an apparatus decreases over time within an allowablerange.

Technical Solution

A first aspect of a plant state monitoring method of monitoring anoperation state of a plant using a Mahalanobis distance based on thequantity of state of the plant according to the present invention atleast includes: creating a first unit space, which is a set of dataserving as a standard for determining whether or not the operation stateof the plant during a start operation period is normal, based on thequantity of state of the plant during the start operation period; andcreating a second unit space, which is a set of data serving as astandard for determining whether or not the operation state of the plantduring a load operation period is normal, based on the quantity of stateof the plant during the load operation period.

In the first aspect of the plant state monitoring method according tothe present invention, data of the second unit space may be collectedfrom both when the load of the plant varies and when a rated load isapplied.

In the first aspect of the plant state monitoring method according tothe present invention, the first unit space may be created based on thequantity of state of the plant acquired during a period from the timethat is a first time before the time when the state of the plant isevaluated during the start operation period of the plant to the timethat is a second time before that time. In addition, the second unitspace may be created based on the quantity of state of the plantacquired during a period from the time that is a third time before thetime when the state of the plant is evaluated during the load operationperiod of the plant to the time that is a fourth time before that time.

In the first aspect of the plant state monitoring method according tothe present invention, the first unit space and the second unit spacemay be created based on the quantity of state which is periodicallycollected at predetermined time intervals.

A first aspect of a plant state monitoring computer program according tothe present invention is executed by a computer of a plant statemonitoring apparatus which monitors an operation state of a plant usinga Mahalanobis distance based on the quantity of state of the plant. Theplant state monitoring computer program at least includes: creating afirst unit space, which is a set of data serving as a standard fordetermining whether or not the state of the plant during a startoperation period is normal, based on the quantity of state of the plantduring the start operation period and creating a second unit space,which is a set of data serving as a standard for determining whether ornot the state of the plant during a load operation period is normal,based on the quantity of state of the plant during the load operationperiod; calculating the Mahalanobis distance based on the quantity ofstate of the plant, acquired when the state of the plant is evaluated;and determining the state of the plant based on the Mahalanobis distanceand a predetermined threshold value obtained from the first and secondunit spaces.

In the first aspect of the plant state monitoring computer programaccording to the present invention, the first unit space may be createdbased on the quantity of state of the plant acquired during a periodfrom the time that is a first time before the time when the state of theplant is evaluated during the start operation period of the plant to thetime that is a second time before that time. In addition, the secondunit space may be created based on the quantity of state of the plantacquired during a period from the time that is a third time before thetime when the state of the plant is evaluated during the load operationperiod of the plant to the time that is a fourth time before that time.

A plant state monitoring apparatus for monitoring an operation state ofa plant using a Mahalanobis distance based on the quantity of state ofthe plant according to the present invention at least includes: a unitspace creating unit which creates a first unit space, which is a set ofdata serving as a standard for determining whether or not the state ofthe plant during a start operation period is normal, based on thequantity of state of the plant during the start operation period, andcreates a second unit space, which is a set of data serving as astandard for determining whether or not the state of the plant during aload operation period is normal, based on the quantity of state of theplant during the load operation period; a Mahalanobis distancecalculating unit which calculates the Mahalanobis distance based on thequantity of state of the plant, acquired when the state of the plant isevaluated; and a plate state determining unit which determines the stateof the plant based on the Mahalanobis distance calculated by theMahalanobis distance calculating unit and a predetermined thresholdvalue obtained from the first and second unit spaces created by the unitspace creating unit.

In the first aspect of the plant state monitoring apparatus according tothe present invention, the unit space creating unit may create the firstunit space based on the quantity of state of the plant acquired during aperiod from the time that is a first time before the time when the stateof the plant is evaluated during the start operation period of the plantto the time that is a second time before that time. In addition, theunit space creating unit may create the second unit space based on thequantity of state of the plant acquired during a period from the timethat is a third time before the time when the state of the plant isevaluated during the load operation period of the plant to the time thatis a fourth time before that time.

A second aspect of the plant state monitoring method of monitoring anoperation state of a plant according to the present invention at leastincludes: creating a third unit space, which is a set of data serving asa standard for determining whether or not the operation state of theplant is normal, based on the quantity of state of the plant during aperiod from the time that is a fifth time before the time when the stateof the plant is evaluated to the time that is a sixth time before thattime.

A third aspect of a plant state monitoring method of monitoring anoperation state of a plant using a Mahalanobis distance related to thequantity of state of the plant according to the present invention atleast includes: acquiring from the plant the quantity of state forcreating a unit space of the plant, which is used to create a third unitspace which is a set of data serving as a standard for determiningwhether or not the operation state of the plant is normal; acquiring thequantity of state of the plant when the state of the plant is evaluated;calculating the Mahalanobis distance based on the acquired quantity ofstate; and determining the state of the plant based on the calculatedMahalanobis distance and a predetermined threshold value. The third unitspace is created based on the quantity of state of the plant during aperiod from the time that is a fifth time before the time when the stateof the plant is evaluated to the time that is a sixth time before thattime.

A second aspect of a plant state monitoring apparatus for monitoring anoperation state of a plant according to the present invention at leastincludes: a unit space creating unit which creates a third unit space,which is a set of data serving as a standard for determining whether ornot the state of the plant is normal or abnormal, based on the quantityof state of the plant during a period from the time that is a fifth timebefore the time when the state of the plant is evaluated to the timethat is a sixth time before that time; a Mahalanobis distancecalculating unit which calculates a Mahalanobis distance based on thequantity of state of the plant, acquired when the state of the plant isevaluated; and a plate state determining unit which determines the stateof the plant based on the Mahalanobis distance calculated by theMahalanobis distance calculating unit and a predetermined thresholdvalue obtained from the third unit space created by the unit spacecreating unit.

As such, a unit space, which is a set of data serving as a standard fordetermining whether the state of the plant is normal or abnormal, iscreated based on the quantity of state of the plant during the periodfrom the time that is a predetermined time before the time when thestate of the plant is evaluated to the time that is a predetermined timebefore that time. In this way, the period for which information used tocreate the unit space is acquired is moved with the progress ofevaluation. Therefore, even when the quantity of state is changed due toa variation in the performance of an apparatus over time in addition toseason variations, it is possible to create the unit space inconsideration of the influence of the variation. As a result, it ispossible to prevent a reduction in the accuracy of determining the stateof a gas turbine power generation plant and accurately determine whetherthe state of the gas turbine power generation plant is normal orabnormal. Here, a set of data, which is a standard for determiningwhether the state of the plant is normal or abnormal, is used tocalculate the Mahalanobis distance or determine whether the plant is ina normal state or an abnormal state, and is called a unit space.

In the plant state monitoring method or the plant state monitoringapparatus, the quantity of state of the plant, at any time or aplurality of times in one solid day within the period for which thequantity of state is collected may be used as the quantity of state ofthe plant, that is, the quantity of state for creating a unit space,acquired during a period from the time that is a fifth time before thetime when the state of the plant is evaluated to the time that is asixth time before that time. In this way, it is possible to reduce thequantity of state of the plant used to create a unit space, which is aset of data serving as a standard for determining whether the state ofthe plant is normal or abnormal.

In the plant state monitoring method or the plant state monitoringapparatus according to the present invention, the previous quantities ofstate for creating a unit space are excluded in chronological order fromthe creation of the unit space, such that the oldest one is excludedfirst.

The period for which the quantity of state (the quantity of state forcreating a unit space) used to create the unit space is acquired ismoved with the progress of evaluation. That is, the period is moved overtime. The quantity of state for creating a unit space corresponding tothe time elapsed is excluded in chronological order from the creation ofthe unit space such that the oldest one is excluded first, and new unitspace is created whenever the state of the plant is evaluated. As such,the period for which information (the quantity of state for creating aunit space) used to create the unit space is acquired is moved with theprogress of evaluation, and old information is removed. Therefore, forexample, even when the quantity of state is changed due to a variationin the state of parts, such as abrasion, over time, it is possible tocreate the unit space in consideration of the influence of thevariation. As a result, even when the quantity of state is changed dueto allowed and assumed factors, such as variation over time, in additionto a season variation, it is possible to accurately determine whetherthe state of a plant is normal or abnormal.

A second aspect of a plant state monitoring computer program accordingto the present invention is executed by a computer of a plant statemonitoring apparatus which monitors an operation state of a plant. Theplant state monitoring computer program allows the computer to create athird unit space, which is a set of data serving as a standard fordetermining whether or not the operation state of the plant is normal,based on the quantity of state of the plant during a period from thetime that is a fifth time before the time when the state of the plant isevaluated to the time that is a sixth time before that time.

A third aspect of a plant state monitoring computer program according tothe present invention is executed by a computer of a plant statemonitoring apparatus which monitors an operation state of a plant usinga Mahalanobis distance related to the quantity of state of the plant.The plant state monitoring computer program at least includes: acquiringfrom the plant the quantity of state for creating a unit space of theplant, which is used to create a third unit space which is a set of dataserving as a standard for determining whether or not the operation stateof the plant is normal; acquiring the quantity of state of the plantwhen the state of the plant is evaluated; calculating the Mahalanobisdistance based on the acquired quantity of state; and determining thestate of the plant based on the calculated Mahalanobis distance and apredetermined threshold value. The third unit space is created based onthe quantity of state of the plant during a period from the time that isa fifth time before the time when the state of the plant is evaluated tothe time that is a sixth time before that time.

Advantageous Effects

According to the invention, it is possible to accurately determinewhether the operation state of a plant is normal or abnormal when astart operation is performed under operation conditions different fromthose when a rated load is applied, and when the performance of anapparatus decreases over time within an allowable range.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram schematically illustrating an example of thestructure of a plant state monitoring apparatus according to a firstembodiment of the present invention.

FIG. 2 is a conceptual diagram illustrating a unit space of a plantstate monitoring method according to the first embodiment.

FIG. 3 is a flowchart illustrating the procedure of the plant statemonitoring method according to the first embodiment.

FIG. 4 is a conceptual diagram illustrating the concept of theMahalanobis distance.

FIG. 5 is a conceptual diagram illustrating a variation in theMahalanobis distance over time.

FIG. 6 is a conceptual diagram illustrating a method of creating theunit space in the plant state monitoring method according to the firstembodiment.

FIG. 7 is a flowchart illustrating the procedure of a plant statemonitoring method according to a second embodiment.

EXPLANATION OF REFERENCE

-   1 GAS TURBINE POWER GENERATION PLANT-   2 COMPRESSOR-   3 COMBUSTOR-   4 TURBINE-   5 POWER GENERATOR-   6 GAS TURBINE-   10 PLANT STATE MONITORING APPARATUS-   11 INPUT/OUTPUT UNIT-   12 PROCESSING UNIT-   12 a UNIT SPACE CREATING UNIT-   12 b MAHALANOBIS DISTANCE CALCULATING UNIT-   12 c PLANT STATE DETERMINING UNIT-   13 STORAGE UNIT-   14 CONTROL PANEL

BEST MODE FOR CARRYING OUT THE INVENTION First Embodiment

Hereinafter, a first embodiment of the invention will be described withreference to the accompanying drawings. The invention is not limited tothe following exemplary embodiments (hereinafter, referred to asembodiments). The following embodiments include components that can beeasily assumed by those skilled in the art, substantially the samecomponents, and components in the equivalent range. In this embodiment,an example in which the invention is applied to a technique formonitoring the state of a gas turbine power generation plant will bedescribed, but the invention is not limited thereto. For example, theinvention can be applied to all plants requiring the monitoring of aplurality of state quantities, such as a nuclear power generation plantand a chemical plant.

This embodiment is characterized in that the entire gas turbineoperation period is divided into two periods, that is, a start operationperiod (less than a rated speed) and a rated speed operation period (atleast the rated speed; generally, a load operation), the quantity ofstate during each period is monitored, it is determined whether thestate of a plant is normal or abnormal based on the Mahalanobisdistance, and a unit space used to calculate the Mahalanobis distance ordetermine whether the state of the plant is normal or abnormal iscreated for each of the two operation periods, that is, the startoperation period and the rated speed operation period, based on thequantity of state of the plant.

FIG. 1 is a diagram schematically illustrating an example of thestructure of a plant state monitoring apparatus according to thisembodiment. A plant state monitoring apparatus 10 monitors the state(operation state) of a power generation plant (gas turbine powergeneration plant) 1 using a gas turbine 6 and determines whether or notthe gas turbine power generation plant 1 is normally operated. If it isdetermined that the gas turbine power generation plant 1 is not normallyoperated, the plant state monitoring apparatus 10 notifies it orspecifies the quantity of state that has been determined to be abnormal(for example, the temperature or pressure of each unit of the gasturbine 6).

The gas turbine power generation plant 1 to be monitored drives a powergenerator 5 using the gas turbine 6 to generate power. The gas turbine 6includes a compressor 2, a combustor 3, and a turbine 4 that rotates thecompressor 2. The compressor 2 compresses air drawn from an inlet of thecompressor 2 to generate a high-temperature and high-pressure air andsupplies the air to the combustor 3. In the combustor 3, fuel issupplied to the high-temperature and high-pressure air and is turnedout. When the fuel is burned out in the combustor 3, a high-temperatureand high-pressure combustion gas is generated and supplied to theturbine 4, and the turbine 4 is driven. In this way, the turbine 4 isrotated.

An output shaft of the gas turbine 6, that is, rotating shafts of theturbine 4 and the compressor 2 are connected to the power generator 5.Therefore, when the gas turbine 6 is operated to rotate the turbine 4,the output of the turbine is transmitted to the power generator 5. Inthis way, the gas turbine 6 drives the power generator 5 such that thepower generator 5 generates power.

The plant state monitoring apparatus 10 monitors the state of the gasturbine power generation plant 1. In this embodiment, the plant statemonitoring apparatus 10 monitors the state of one gas turbine powergeneration plant 1, but it may monitor the operation states of aplurality of gas turbine power generation plants 1. The plant statemonitoring apparatus 10 is, for example, a computer and includes aninput/output unit (I/O) 11, a processing unit 12, and a storage unit 13.The plant state monitoring apparatus 10 may be a so-called personalcomputer, or a combination of a CPU (Central Processing Unit) and amemory.

The processing unit 12 receives the quantity of state of the gas turbinepower generation plant 1 from various kinds of state quantity detectingunits (for example, sensors) that are attached to the gas turbine powergeneration plant 1 through the input/output unit 11. Various kinds ofstate quantity detecting units periodically acquire the correspondingquantities of state at a predetermined time interval from the start ofan operation, and input the acquired quantities of state to theprocessing unit 12 through the input/output unit 11. The quantities ofstate of the gas turbine power generation plant 1 include, for example,the output of the power generator 5, the temperature of air drawn to thecompressor 2, the temperature of each unit of the gas turbine 6,pressure, vibration, and a rotation speed. When the state of the gasturbine power generation plant 1 is monitored, for example, about 50 to60 state quantities are used. The quantity of state of the gas turbinepower generation plant 1 is transmitted to the processing unit 12 of theplant state monitoring apparatus 10 in the form of electric signals. Theprocessing unit 12 includes, for example, a CPU and sequentially readsprograms (computer program) or a sequence of call instructions from thestorage unit 13, analyzes them, and moves or processes data based on theanalysis result.

The processing unit 12 may be implemented by dedicated hardware. Inaddition, the following structure may be used: a computer program forimplementing the function of the processing unit 12 is recorded on acomputer-readable recording medium; and a computer system reads andexecutes the computer program recorded on the recording medium toperform the procedure of a plant state monitoring method according tothis embodiment. The ‘computer system’ includes an OS and hardware, suchas peripheral devices.

The ‘computer-readable recording medium’ means a portable medium, suchas a flexible disk, a magneto-optical disk, a ROM, or a CD-ROM, or arecording device, such as a hard disk provided in the computer system.In addition, the ‘computer-readable recording medium’ includes a mediumthat dynamically stores a computer program in a short time, such as acommunication line when the computer program is transmitted through theInternet or a communication line, such as a telephone line, and a mediumthat stores the computer program for a predetermined period of time,such as a volatile memory provided in a server or a computer system,serving as a client. The computer program may implement some of theabove-mentioned functions, or it may be combined with the computerprogram recorded on the computer system to implement the above-mentionedfunctions.

The plant state monitoring method according to this embodiment may beperformed by allowing a computer, such as a personal computer or aworkstation, to execute the computer program. The computer program maybe distributed through a communication line, such as the Internet. Thecomputer program may be recorded on a computer readable recordingmedium, such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or aDVD, and the computer may read the computer program from the recordingmedium and execute it.

The processing unit 12 includes a unit space creating unit 12 a, whichis a unit space creating portion, a Mahalanobis distance calculatingunit 12 b, which is a Mahalanobis distance calculating portion, and aplant state determining unit 12 c, which is a plant state determiningportion. The functions of the plant state monitoring apparatus 10according to this embodiment are implemented by the unit space creatingunit 12 a, the Mahalanobis distance calculating unit 12 b, and the plantstate determining unit 12 c. The unit space creating unit 12 a creates aunit space using the plant state monitoring method according to thisembodiment from the electric signals related to the state of the gasturbine power generation plant 1, which are acquired through theinput/output unit 11, based on a state value (state value for creating aunit space) for creating a Mahalanobis unit space. The unit space is aset of data, which is a standard for determining whether the state ofthe gas turbine power generation plant 1 is normal or abnormal. In thisembodiment, a unit space for startup (that is, a first unit space),which is a set of data serving as a standard for determining whether theoperation state of the gas turbine power generation plant 1 during thestart operation period is normal or abnormal, is created based on thequantity of state of the plant during the start operation period. Inaddition, a unit space for a rated speed (that is, a second unit space),which is a set of data serving as a standard for determining whether theoperation state of the gas turbine power generation plant 1 during theload operation period is normal or abnormal, is created based on thequantity of state of the plant during the load operation period.

The Mahalanobis distance calculating unit 12 b calculates theMahalanobis distance from the unit space created by the unit spacecreating unit 12 a and the state value of the gas turbine powergeneration plant 1 acquired when the state of the gas turbine powergeneration plant 1 is evaluated. The plant state determining unit 12 cdetermines the state of the gas turbine power generation plant 1 basedon the Mahalanobis distance calculated by the Mahalanobis distancecalculating unit 12 b and a predetermined threshold value obtained fromthe unit space that is created by the unit space creating unit 12 a.

A control panel 14, which is an output unit, is connected to theinput/output unit 11 of the plant state monitoring apparatus 10. Thecontrol panel 14 includes a display 14D, which is a display unit, and aninput unit 14C that is used to input instructions to the plant statemonitoring apparatus 10. The storage unit 13 of the plant statemonitoring apparatus 10 includes, for example, a volatile memory, suchas a RAM (Random Access Memory), a non-volatile memory, such as a ROM(Read Only Memory), a computer-readable storage medium, such as a harddisk device, a magneto-optical disk device, or a CD-ROM, or combinationsthereof. The storage unit 13 stores, for example, data or a computerprogram for implementing the plant state monitoring method according tothis embodiment. The processing unit 12 uses the computer program or thedata to implement the plant state monitoring method according to thisembodiment or control the operation of the gas turbine power generationplant 1. The storage unit 13 may be provided outside the plant statemonitoring apparatus 10 and the plant state monitoring apparatus 10 mayaccess the storage unit 13 through a communication line.

FIG. 2 is a conceptual diagram illustrating the unit space in the plantstate monitoring method according to this embodiment. A lower side ofthe FIG. 2 shows an example of a variation in the rotation speed of thegas turbine over time, and an upper side thereof shows an example of avariation in the output of the power generator 5 over time. The gasturbine 6 is driven by a start motor. When the gas turbine 6 reaches apredetermined rotation speed, the fuel burned by the combustor 3 issupplied to the turbine 4 and the gas turbine 6 reaches a rated rotationspeed while increasing the rotation speed. Then, the gas turbine 6 isoperated while maintaining the rated rotation speed. In this case, theperiod over which the gas turbine 6 reaches the rated speed is referredto as the start operation period, and the period in which the gasturbine 6 is at a rated speed is referred to as the rated speedoperation period.

In this embodiment, the unit spaces (the unit space for startup and theunit space for a rated speed) used to calculate the Mahalanobis distanceor to determine whether the state of the plant is normal or abnormal arecreated from two operation periods, such as the start operation periodand the rated speed operation period. In addition, data for creating aunit section is acquired from both during the load change periods L1,L3, and L5 for which the output shown on the upper side of FIG. 2 ischanged and during the constant load periods L2 and L4 for which asubstantially constant output is generated in the unit rated speedoperation period, and the unit space is created on the acquired data(only the constant load periods L2 and L4 in the related art).

FIG. 3 is a flowchart illustrating the procedure of the plant statemonitoring method according to this embodiment.

FIG. 4 is a conceptual diagram illustrating the concept of theMahalanobis distance. FIG. 5 is a conceptual diagram illustrating avariation in the Mahalanobis distance over time. FIG. 6 is a conceptualdiagram illustrating a method of creating the unit space in the plantstate monitoring method according to this embodiment. In the plant statemonitoring method according to this embodiment, when it is determinedwhether the state of the gas turbine power generation plant 1 is normalor abnormal based on a plurality of state quantities, it is determinedwhether the state of the gas turbine power generation plant 1 is normalor abnormal based on the Mahalanobis distance. The Mahalanobis distancehas been widely used as a factor for processing a plurality of variables(the quantities of state).

When it is determined whether the gas turbine power generation plant 1is normal or abnormal based on the Mahalanobis distance, the Mahalanobisdistance is used to convert multi-dimensional data into one-dimensionaldata. The difference between the unit space and a signal space (dataother than the unit space: for example, the quantity of state when thestate of the gas turbine power generation plant 1 is evaluated) isregarded as the Mahalanobis distance. In this embodiment, theMahalanobis distance of the signal space is calculated by using thematrix formed from the unit space. In this way, it is possible torepresent the abnormality of data. Next, the Mahalanobis distance willbe described.

The total sum of a plurality of state quantities indicating the state ofthe gas turbine power generation plant 1 is u, each quantity of state isallocated to a variable X, and u quantities of state are defined byvariables X1 to Xu (u is an integer at least 2). In the operation stateof the gas turbine power generation plant 1, which is a reference, atotal of v (2 or more) quantities of state (the quantities of state forcreating a unit space) with variables X1 to Xu are collected. In thisembodiment, the unit space for startup is created based on the quantityof state (that is, the quantity of state for creating a unit space) ofthe gas turbine power generation plant 1 collected during the periodfrom the time that is a predetermined time (a first time) before thetime when the state of the gas turbine power generation plant 1 isevaluated during the start operation of the gas turbine power generationplant 1 to the time that is a predetermined time (that is, a secondtime) before that time.

In addition, the unit space for a rated speed is created based on thequantity of state (that is, the quantity of state for creating a unitspace) of the gas turbine power generation plant 1 collected during theperiod from the time that is a predetermined time (third time) beforethe time when the state of the gas turbine power generation plant 1 isevaluated during the rated speed operation of the gas turbine powergeneration plant 1 to the time that is a predetermined time (that is, afourth time) before that time.

Therefore, the operation state of the gas turbine power generation plant1 is acquired during the state quantity collection period from the timethat is a predetermined time before the time when the state of the gasturbine power generation plant 1 is evaluated to the time that is apredetermined time before that time. In the following description, theunit space indicates the unit space for startup during the startoperation period and the unit space for a rated speed during the ratedspeed operation period.

The average value Mi and the standard deviation σi (the degree ofvariation of reference data) of each of the variables X1 to Xu arecalculated by the following Expressions 1 and 2. In Expressions 1 and 2,i indicates the number of items (the number of quantities of state:integer) and is set to 1 to u corresponding to the variables X1 to Xu, jis any one of 1 to v (integer), and v indicates the number of quantitiesof state. For example, when 60 quantities of state are acquired, v is60. The standard deviation is the square root of an expectation value,which is the square of the difference between the quantity of state andthe average value thereof.

$\begin{matrix}{M_{i} = {\frac{1}{v}{\sum\limits_{j = 1}^{v}\; X_{ij}}}} & \left\lbrack {{Expression}\mspace{14mu} 1} \right\rbrack \\{\sigma_{i} = \sqrt{\frac{1}{v - 1}{\sum\limits_{j = 1}^{v}\; \left( {X_{ij} - M_{i}} \right)^{2}}}} & \left\lbrack {{Expression}\mspace{14mu} 2} \right\rbrack\end{matrix}$

Then, a standardizing process of converting the original variables X1 toXu into x1 to xu based on the calculated average value Mi and standarddeviation σi, which are the quantities of state indicatingcharacteristics, using the following Expression 3 is performed. That is,the quantity of state of the gas turbine power generation plant 1 isconverted into a random variable with an average of 0 and a standarddeviation of 1. In the following Expression 3, j is any one of 1 to v(integer), and v indicates the number of quantities of state.

x _(ij)=(X _(ij) −M _(i))/σ_(i)  [Expression 3]

Then, in order to perform analysis with data obtained by standardizing avariate into an average of 0 and a variance of 1, the correlationbetween the variables X1 to Xu, that is, a covariance matrix(correlation matrix) R indicating the relation between the variates, andan inverse matrix R⁻¹ of the covariance matrix (correlation matrix) aredefined by the following Expression 4. In the following Expression 4, kindicates the number of items (the number of quantities of state) (inthis embodiment, the number of items is u), and i and p each indicatethe value of each quantity of state (in this embodiment, i and p are inthe range of 1 to u).

$\begin{matrix}{\mspace{79mu} {{R = \begin{pmatrix}1 & r_{12} & \ldots & r_{1\; k} \\r_{21} & 1 & \ldots & r_{2\; k} \\\vdots & \vdots & \ddots & \vdots \\r_{k\; 1} & r_{k\; 2} & \ldots & 1\end{pmatrix}}{R^{- 1} = {\begin{pmatrix}a_{11} & a_{12} & \ldots & a_{1\; k} \\a_{21} & a_{22} & \ldots & a_{2\; k} \\\vdots & \vdots & \ddots & \vdots \\a_{k\; 1} & a_{k\; 2} & \ldots & a_{kk}\end{pmatrix} = \begin{pmatrix}1 & r_{12} & \ldots & r_{1\; k} \\r_{21} & 1 & \ldots & r_{2\; k} \\\vdots & \vdots & \ddots & \vdots \\r_{k\; 1} & r_{k\; 2} & \ldots & 1\end{pmatrix}^{- 1}}}\mspace{20mu} {r_{ip} = {r_{pi} = {\frac{1}{v}{\sum\limits_{j = 1}^{v}\; {X_{ij}X_{pj}}}}}}}} & \left\lbrack {{Expression}\mspace{14mu} 4} \right\rbrack\end{matrix}$

After the above-mentioned calculation is performed, the Mahalanobisdistance D, which is the quantity of state indicating characteristics,is calculated by the following Expression 5. In the following Expression5, j is any one of 1 to v (integer), and v indicates the number ofquantities of state. In addition, k indicates the number of items (thenumber of quantities of state) (in this embodiment, the number of itemsis u) and a₁₁ to a_(kk) indicate coefficients of the inverse matrix R⁻¹of the covariance matrix R in Expression 4.

$\begin{matrix}{D_{j}^{2} = {{\frac{1}{k}{\left( {x_{ij},x_{2\; j},\ldots \mspace{14mu},x_{kj}} \right) \cdot \begin{pmatrix}a_{11} & a_{12} & \ldots & a_{1\; k} \\a_{21} & a_{22} & \ldots & a_{2\; k} \\\vdots & \vdots & \ddots & \vdots \\a_{k\; 1} & a_{k\; 2} & \ldots & a_{kk}\end{pmatrix} \cdot \begin{pmatrix}x_{1\; j} \\x_{2\; j} \\\vdots \\x_{kj}\end{pmatrix}}} = {{\frac{1}{k}{\sum\limits_{i = 1}^{k}\; {\sum\limits_{p = 1}^{k}\; {a_{ip}x_{ij}x_{pj}}}}} = {\frac{1}{k}{\left( {x_{1\; j},x_{2\; j},\ldots \mspace{14mu},x_{kj}} \right) \cdot R^{- 1} \cdot \begin{pmatrix}x_{1\; j} \\x_{2\; j} \\\vdots \\x_{kj}\end{pmatrix}}}}}} & \left\lbrack {{Expression}\mspace{14mu} 5} \right\rbrack\end{matrix}$

The Mahalanobis distance D is substantially at most 4 when referencedata, that is, the average value of the unit space is 1 and the quantityof state of the gas turbine power generation plant 1 is normal. However,when the quantity of state of the gas turbine power generation plant 1is abnormal, the value of the Mahalanobis distance D is increased. Assuch, the value of the Mahalanobis distance D is increased according tothe degree of abnormality of the quantity of state of the gas turbinepower generation plant 1 (the distance from the unit space).

Next, the procedure of the plant state monitoring method according tothis embodiment will be described. The plant state monitoring methodaccording to this embodiment can be implemented by the plant statemonitoring apparatus 10 shown in FIG. 1. First, as shown in FIG. 2, inStep S100, the plant state monitoring apparatus 10 sets threshold valuesRm and Rr, or sets predetermined values as the threshold values Rm andRr. In this embodiment, the threshold value Rm is 300 rpm, and thethreshold value Rr is 2940 rpm. Then, the plant state monitoringapparatus 10 measures the rotation speed R in Step S101 and determineswhether the rotation speed R is at most the threshold value Rm in StepS102. If it is determined that the rotation speed R is at least thethreshold value Rm, the plant state monitoring apparatus 10 determineswhether the measured rotation speed R is less than the threshold valueRr in Step S103. That is, the plant state monitoring apparatus 10determines whether the operation period is the start operation period orthe rated speed operation period shown in FIG. 2.

When the rotation speed R is at least the threshold value Rm, the plantstate monitoring apparatus 10 returns to Step S101 and measures therotation speed R again. Then, the plant state monitoring apparatus 10repeatedly performs the process of determining whether the operationperiod is the start operation period or the rated speed operationperiod. When the rotation speed R is at least the threshold value Rm andis less than the threshold value Rr, it is determined that the operationperiod is the start operation period. In Step S104, the quantity ofstate is acquired from the unit space for startup. When the rotationspeed R is at least the threshold value Rm and is at least the thresholdvalue Rr, it is determined that the operation period is the rated speedoperation period. In Step S105, the quantity of state is acquired fromthe unit space for a rated speed. That is, in the following process,during the period for which the rotation speed R is at least thethreshold value Rm and is less than the threshold value Rr, it isdetermined whether the state is normal or abnormal by the unit space forstartup. During the period for which the rotation speed R is at leastthe threshold value Rr, it is determined whether the state is normal orabnormal based on the unit space for a rated speed.

In Step S106, the unit space creating unit 12 a of the plant statemonitoring apparatus 10 acquires the quantity of state of the gasturbine power generation plant 1 during the current state quantityacquisition period. The quantity of state of the gas turbine powergeneration plant 1 is acquired during an operation, but the quantity ofstate is not necessarily acquired during the operation of the gasturbine power generation plant 1. For example, the quantity of state isperiodically acquired from various kinds of sensors that are attached tothe gas turbine power generation plant 1 at a predetermined timeinterval and is then stored in the storage unit 13 of the plant statemonitoring apparatus 10. Therefore, the quantity of state is acquired ata predetermined time interval during both the start operation period andthe rated speed operation period after a startup and during both theload change periods L1, L3, and L5 and the constant load periods L2 andL4 in the rated speed operation period.

In Step S107, it is determined whether or not the unit space is createdduring the current operation period at the operation day. That is, whenthe quantity of state is acquired during the start operation period inStep S104 based on the determination results in Steps S102 and S103, itis determined whether the unit space for startup is created. When theunit space for startup is not created at the operation day, the processproceeds to Step S108. On the other hand, when the unit space forstartup has already been created, the following Steps S108 and S109 areomitted and the process proceeds to Step S110. Similarly, when thequantity of state is acquired during the rated speed operation period inStep S105 based on the determination results in Steps S102 and S103, itis determined whether the unit space for a rated speed is created. Whenthe unit space for a rated speed is not created, the process proceeds toStep S108. On the other hand, when the unit space for a rated speed hasalready been created, the process proceeds to Step S110.

When the unit space is not created during each operation period, in StepS108, the unit space creating unit 12 a acquires the quantity of statefor creating a unit space. That is, the unit space creating unit 12 aacquires a unit space state quantity for startup during the startoperation period and a unit space state quantity for a rated speedduring the rated speed operation period. The quantity of state forcreating a unit space is selected from the quantity of state of the gasturbine power generation plant 1 that has been acquired in Step S106 andstored in the storage unit 13. In this embodiment, the unit space forstartup or the unit space for a rated speed is created based on thequantity of state of the gas turbine power generation plant 1 collectedduring the period from the time that is a predetermined time before thetime when the state of the gas turbine power generation plant 1 isevaluated to the time that is a predetermined time before that time.

That is, the unit space for startup is created based on the quantity ofstate of the gas turbine power generation plant 1 collected during theperiod from the time that is a predetermined time (first time) beforethe time when the state of the gas turbine power generation plant 1 isevaluated during the start operation of the gas turbine power generationplant 1 to the time that is a predetermined time (second time) beforethe first time. In addition, the unit space for a rated speed is createdbased on the quantity of state of the gas turbine power generation plant1 collected during the period from the time that is a predetermined time(third time) before the time when the state of the gas turbine powergeneration plant 1 is evaluated during the rated speed operation of thegas turbine power generation plant 1 to the time that is a predeterminedtime (that is, a fourth time) before the third time.

For example, the time when the state of the gas turbine power generationplant 1 is evaluated (referred to as ‘during evaluation’) is an N-th dayshown in FIG. 6, one predetermined time (the first time or the thirdtime) is m days, and the other predetermined time (the second time orthe fourth time) is n days. It is assumed that the period from the timethat is m days before the evaluation to the time that is n days beforethat time is referred to as a period for which the quantity of state ofthe gas turbine power generation plant 1 is collected. In this case, aunit space A(N) is created based on the quantity of state of the gasturbine power generation plant 1 acquired for n days from the time thatis m+n days before the N-th day to the time that is m days before theN-th day. Similarly, when the evaluation is performed at an (N+1)-thday, a unit space A(N+1) is created based on the quantity of state ofthe gas turbine power generation plant 1 acquired for n days from thetime that is m+n days before the (N+1)-th day to the time that is m daysbefore the (N+1)-th day. When the evaluation is performed at an (N+2)-thday, a unit space A(N+2) is created based on the quantity of state ofthe gas turbine power generation plant 1 acquired for n days from thetime that is m+n days before the (N+2)-th day to the time that is m daysbefore the (N+2)-th day.

When the N-th day is a reference point and the evaluation is performedat the (N+1)-th day, the unit space A(N+1) is created based on thequantity of state of the gas turbine power generation plant 1 acquiredfor n days from the time that is (m+n−1) days before the N-th day to thetime that is m days before the (N+1)-th day. When the evaluation isperformed at an (N+2)-th day, a unit space A(N+2) is created based onthe quantity of state of the gas turbine power generation plant 1acquired for n days from the time that is (m+n−2) days before the N-thday to the time that is m days before the (N+2)-th day.

For example, when predetermined m+n days have not elapsed from the dayat which the gas turbine power generation plant 1 was installed andoperated, it is difficult to perform the above-mentioned process tocreate the unit space. Therefore, in this case, until n days haveelapsed from the start of the operation, the unit space may be createdbased on the quantity of state acquired each day. In addition, until ndays or more, for example, m+n days have elapsed, the unit space may becreated based on the quantity of state acquired during the period fromthe day at which the operation starts to n days.

In this embodiment, the unit space is created based on the quantity ofstate acquired during a predetermined period (in this embodiment, ndays) before the evaluation. In the creation of the unit space, newquantity of state is acquired as data every day over time. In addition,when a time corresponding to the evaluation has elapsed, the previousquantities of state are sequentially removed in chronological order fromthe creation of the unit space. As described above, when evaluation isperformed at the N-th day, the unit space A(N) is created based on thequantity of state of the gas turbine power generation plant 1 acquiredfor n days from the time that is m days before the evaluation to thetime that is n days before that time. When evaluation is performed atthe (N+1)-th day after one full day (24 hours) has elapsed from the N-thday, the unit space A(N+1) is created based on the quantity of state ofthe gas turbine power generation plant 1 acquired for n days from thetime that is m−1 days before the N-th day to the time that is n daysbefore that time. That is, when the evaluation time is changed from theN-th day to the (N+1)-th day, the quantity of state that has not beencollected at the N-th day where the evaluation is performed, that is,the quantity of state collected for one day from the time that is m−1days before the N-th day to the time that is one day before that time isused to create the unit space A(N+1). In addition, the quantity of statethat has been collected at the N-th day where the evaluation isperformed, that is, the quantity of state collected for one day from thetime that is (m+n−1) days before the N-th day to the time that is oneday before that time is removed from the creation of the unit spaceA(N+1).

As such, in this embodiment, the period for which the state value (thequantity of state for creating a unit space) used to create the unitspace is acquired is moved with the progress of evaluation, and a newunit space is created whenever the state of the gas turbine powergeneration plant 1 is evaluated. As such, the period for whichinformation used to create the unit space is acquired is moved with theprogress of evaluation. Therefore, even when the quantity of state ischanged due to a variation in the performance of parts, such asabrasion, over time in addition to a season variation, it is possible tocreate the unit space in consideration of the influence of thevariation. As a result, even when the quantity of state is changed dueto allowed and assumed factors, such as a variation in performance overtime, in addition to the season variation, it is possible to prevent areduction in the accuracy of the determination of the state of the gasturbine power generation plant 1 and accurately determine whether thestate of the gas turbine power generation plant 1 is normal or abnormal.

In the above Patent Citation 1, a plurality of unit spaces is preparedfor each season. However, for example, when abnormal weather conditions,such as cold summer and warm winter, occur, it is difficult to reflectthe influence of the abnormal weather conditions to the unit space. As aresult, in the technique disclosed in the above Patent Citation 1, theaccuracy of the determination of the state of the gas turbine powergeneration plant 1 is lowered, and a normal state is likely to bedetermined to be an abnormal state. In this embodiment, since the periodfor which information used to create the unit space is moved with theprogress of the evaluation, it is possible to reflect the influence of,for example, the abnormal weather conditions to the unit space. As aresult, it is possible to prevent a reduction in the accuracy of thedetermination of the state of the gas turbine power generation plant 1and accurately determine whether the state of the gas turbine powergeneration plant 1 is normal or abnormal.

In addition, in the above Patent Citation 1, it is necessary to preparea plurality of unit spaces for each season. However, in this embodiment,since the period for which the quantity of state (the quantity of statefor creating a unit space) used to create the unit space is moved withthe progress of evaluation, it is not necessary to prepare a pluralityof unit spaces. Therefore, it is possible to reduce the storage area ofthe unit space in the storage unit 13 provided in the plant statemonitoring apparatus 10. As a result, it is possible to effectively usethe hardware resources of the plant state monitoring apparatus 10. Inthis embodiment, since a new unit space is created whenever the gasturbine power generation plant 1 is evaluated, it is possible to createa unit space for each plant. As a result, it is possible to evaluate thestate of each plant in consideration of the characteristics of theplant, which results in an increase in the accuracy of evaluation.

It is preferable that n be at least 30 days and at most 80 days. In thisembodiment, n is 60 days. In addition, it is preferable that m be atleast 3 days and at most 10 days. In this embodiment, m is 10 days.

In this embodiment, the period for which the quantity of state (thequantity of state for creating a unit space) used to create the unitspace is moved with the progress of evaluation. When the quantity ofstate of the gas turbine power generation plant 1 is gradually changedto an abnormal state and the evaluation operation is included in theperiod, the creation of the unit space is affected by an abnormal statequantity. As a result, the accuracy of the determination of the state ofthe gas turbine power generation plant 1 is likely to be reduced. Inthis embodiment, the state value acquired during a predetermined periodbefore evaluation (in this embodiment, for m days before the evaluation)is not used to create the unit time. In this way, the creation of theunit space is less affected by an abnormal state quantity. Therefore,the accuracy of the determination of the state of the gas turbine powergeneration plant 1 is less likely to be reduced. As a result, eventhough abnormality in the quantity of state of the gas turbine powergeneration plant 1 gradually occurs, it is possible to detect theabnormality.

When the quantity of state for creating a unit space is acquired by theabove-mentioned method, the process proceeds to Step S109.

In Step S109, the unit space creating unit 12 a calculates a unit space(that is, the unit space for startup during the start operation periodand the unit space for a rated speed during the rated speed operationperiod) from the quantity of state for creating a unit space acquired inStep S108. In this embodiment, the number of quantities of state is u,and the unit space is a u-dimensional space. Then, the process proceedsto Step S110, and the Mahalanobis distance calculating unit 12 b of theplant state monitoring apparatus 10 calculates the Mahalanobis distanceD during evaluation.

The Mahalanobis distance D is calculated by Expression 5. In this case,the inverse matrix R⁻¹ of the covariance matrix R in Expression 5 iscalculated from data (the quantity of state) of the unit spacecalculated in Step S109. That is, the Mahalanobis distance D iscalculated based on the unit space for startup or the unit space for arated speed that is calculated from the start operation period or theload operation period, which is a target. In Expression 5, x_(kj) isobtained by converting a variable X_(kj) allocated to the quantity ofstate of the gas turbine power generation plant 1 acquired duringevaluation into the random variable of the standard deviation 1 usingExpression 3. Here, k indicates the number (u) of quantities of state,and j indicates the number of quantities of state of the gas turbinepower generation plant 1 acquired during evaluation.

Then, the process proceeds to Step S111 and the threshold value Dc isset. In this case, the order of Step S110 and Step S111 may be changed.As described above, the Mahalanobis distance D is increased as thedistance from the unit space is increased, that is, according to thedegree of abnormality. The Mahalanobis distance D is substantially atmost 4 when the reference data, that is, the average value of the unitspace is 1 and the quantity of state of the gas turbine power generationplant 1 is a normal state. Therefore, for example, the threshold valueDc may be appropriately set to a value that is more than the maximumvalue of the unit space. In addition, the threshold value Dc may be setin consideration of inherent characteristics of the gas turbine powergeneration plant 1 or a variation in the manufacture of the gas turbinepower generation plant 1. The threshold value Dc may be a predeterminedvalue.

FIG. 4 is a diagram illustrating a unit space A created using the outputP of the power generator 5 and the temperature θ of the air drawn intothe compressor 2 as the quantity of state for creating a unit space. InFIG. 4, B indicates the quantity of state, that is, the measured valuesof the output P of the power generator 5 and the temperature θ of theair drawn into the compressor 2. A solid line indicating the unit spaceA indicates the threshold value Dc. In addition, D indicates theMahalanobis distance. When the quantity of state (in FIG. 4, the outputP and the temperature θ of the air drawn) during evaluation is withinthe threshold value Dc (G in FIG. 4), it can be determined that the gasturbine power generation plant 1 is in a normal state. When the quantityof state during evaluation is more than the threshold value Dc (E and Fin FIG. 4), it can be determined that the gas turbine power generationplant 1 is in an abnormal state. In FIG. 5, since D<Dc is satisfied upto a time T=T6, it is determined that the gas turbine power generationplant 1 is in a normal state. However, since D>Dc is satisfied at a timeT=T7, it is determined that the gas turbine power generation plant 1 isin an abnormal state.

In Step S112, the plant state determining unit 12 c of the plant statemonitoring apparatus 10 compares the Mahalanobis distance D acquired inStep S110 with the threshold value Dc set in Step S111. When thedetermination result in Step S112 is “Yes”, that is, when the plantstate determining unit 12 c determines that the Mahalanobis distance Dis at most the threshold value Dc, it is determined that the gas turbinepower generation plant 1 is in a normal state (Step S113).

When the determination result in Step S112 is “No”, that is, when theplant state determining unit 12 c determines that the Mahalanobisdistance D is more than the threshold value Dc, it is determined thatthe gas turbine power generation plant 1 is in an abnormal state (StepS114). In this case, the process proceeds to Step S115, and the plantstate determining unit 12 c displays the Mahalanobis distance D that hasbeen determined to be abnormal on the display 14D of the control panel14. The displayed Mahalanobis distance D is calculated in Step S110.

Then, the process proceeds to Step S116, and the plant state determiningunit 12 c estimates the items of abnormal state quantities from thedifference between the larger-the-better SN ratios according to whetheror not there are items by, for example, orthogonal table analysis.Whether or not there is an abnormality can be determined from theMahalanobis distance D. However, it is difficult to determine a placewhere an abnormality occurs from the Mahalanobis distance D. It is easyto specify the place where an abnormality occurs or clear up the causeof the abnormality by estimating the items of abnormal state quantities.The plant state determining unit 12 c displays the estimated abnormalstate quantities on the display 14D of the control panel 14. Thedifference between the larger-the-better SN ratios according to whetherthere are items by the orthogonal table analysis is increased in thequantity of state of the abnormal item. Therefore, it is possible tospecify abnormal factors by checking the items with a large differencebetween the larger-the-better SN ratios, for example, the top threeitems. Steps S101 to S116 are repeatedly performed at a predeterminedtime interval until the operation of the gas turbine ends.

According to the above-described embodiment, in different operationconditions, different unit spaces are created from the quantities ofstate corresponding to the start operation period and the rated speedoperation period. When the Mahalanobis distance is calculated, and whenit is determined whether the state of the plant is normal or abnormalbased on the calculated Mahalanobis distance, one of two unit spaces isselected according to whether the period during evaluation is the startoperation period or the rated speed operation period, the Mahalanobisdistance is calculated, and it is determined whether the state of theplant is normal or abnormal. Therefore, it is possible to accuratelydetermine whether the state of the plant is normal or abnormal bothduring the start of the operation and during the application of a ratedload with different operation conditions. During the rated speedoperation period, data is collected from both a case in which a loadvaries and a case in which a constant load is applied. In this way, evenwhen the output varies depending on an output demand during the ratedspeed operation period, it is possible to stably operate a plant usingthe unit space created from the data, without an erroneousdetermination.

As described above, the quantity of state is periodically acquired at apredetermined time interval from the start of the operation, and it isdetermined whether the acquired quantity of state is applied to thestart operation period or the rated speed operation period based on therotation speed when the quantity of state is acquired. Then, the unitspace is created based on the determination result, In addition, theMahalanobis distance is calculated and it is determined whether thestate of the plant is normal or abnormal. That is, it is possible toacquire the quantity of state only by collecting data withoutdesignating a predetermined time or a predetermined number of rotationsto acquire data and without discriminating the start operation periodfrom the rated speed operation period. Therefore, it is possible toreduce the load in the collection of data. During both the startoperation period and the rated speed operation period and during therated speed operation period, it is possible to collect a set of data ata predetermined time interval such that the set of data includes datawhen a load varies and data when a constant load is applied. In thisway, it is possible to appropriately create unit spaces corresponding toeach period.

In addition, the unit space used to calculate the Mahalanobis distanceor determine whether the plant is in a normal state or an abnormal stateis created based on the quantity of state of the plant acquired duringthe period from the time that is a predetermined time before the timewhen the state of the plant is evaluated to the time that is apredetermined time before that time. In this way, the period for whichinformation used to create the unit space is acquired is moved with theprogress of evaluation. Therefore, even when the quantity of state ischanged due to an allowed and assumed factor, for example, variationover time, in addition to a season variation, it is possible to createthe unit space in consideration of the influence of the variation. As aresult, it is possible to reflect factors causing a variation in thequantity of state to the unit space. In this way, it is possible toprevent the accuracy of the determination of the state of a gas turbinepower generation plant from being reduced and accurately determinewhether the gas turbine power generation plant is in a normal state oran abnormal state.

Second Embodiment

Next, a second embodiment of the invention will be described withreference to the drawings. A description of the same structure andcomponents as those in the first embodiment will be omitted. Theinvention is not limited to exemplary embodiments (hereinafter, referredto as embodiments). The following embodiment includes components thatcan be easily assumed by those skilled in the art, substantially thesame components, and components in the equivalent range. In thisembodiment, an example in which the invention is applied to a techniquefor monitoring the state of a gas turbine power generation plant will bedescribed, but the invention is not limited thereto. For example, theinvention can be applied to all plants requiring the monitoring of aplurality of state quantities, such as a nuclear power generation plantand a chemical plant.

In this embodiment, it is determined whether the state of a plant isnormal or abnormal based on the Mahalanobis distance described in thefirst embodiment. In particular, a unit space (that is, a third unitspace) used to calculate the Mahalanobis distance or determine whetherthe plant is in a normal state or an abnormal state is created based onthe quantity of state (that is, the quantity of state for creating aunit space) of the gas turbine power generation plant 1 during theperiod from the time that is a predetermined time (that is, a fifthtime) before the time when the state of the gas turbine power generationplant 1 is evaluated to the time that is a predetermined time (that is,a sixth time) before the fifth time (a detailed description of theMahalanobis distance will be omitted).

Next, the procedure of a plant state monitoring method according to thisembodiment will be described. The plant state monitoring methodaccording to this embodiment is implemented by the plant statemonitoring apparatus 10 shown in FIG. 1 (a detailed description of theplant state monitoring apparatus will be omitted).

FIG. 7 is a flowchart illustrating the procedure of the plant statemonitoring method according to this embodiment.

First, as shown in FIG. 7, in Step S201, the unit space creating unit 12a of the plant state monitoring apparatus 10 acquires the quantity ofstate of the gas turbine power generation plant 1. The quantity of stateof the gas turbine power generation plant 1 is acquired during anoperation, but the quantity of state is not necessarily acquired duringthe operation of the gas turbine power generation plant 1. For example,the quantity of state is periodically acquired from various kinds ofsensors attached to the gas turbine power generation plant 1 at apredetermined time interval and is then stored in the storage unit 13 ofthe plant state monitoring apparatus 10.

Then, the process proceeds to Step S202, and the unit space creatingunit 12 a acquires the quantity of state for creating a unit space. Thequantity of state for creating a unit space is selected from thequantity of state of the gas turbine power generation plant 1 that hasbeen acquired in Step S201 and stored in the storage unit 13. In thisembodiment, the unit space is created based on the quantity of state ofthe gas turbine power generation plant 1 collected during the periodfrom the time that is a predetermined time before the time when thestate of the gas turbine power generation plant 1 is evaluated to thetime that is a predetermined time before that time.

For example, the time when the state of the gas turbine power generationplant 1 is evaluated (referred to as during evaluation) is an N-th dayshown in FIG. 6, one predetermined time (the fifth time) is m days, andthe other predetermined time (the sixth time) is n days. It is assumedthat the period from the time that is m days before the evaluation tothe time that is n days before that time is referred to as a period forwhich the quantity of state of the gas turbine power generation plant 1is collected. In this case, a unit space A(N) is created based on thequantity of state of the gas turbine power generation plant 1 acquiredfor n days from the time that is m+n days before the N-th day to thetime that is m days before the N-th day. Similarly, when the evaluationis performed at an (N+1)-th day, a unit space A(N+1) is created based onthe quantity of state of the gas turbine power generation plant 1acquired for n days from the time that is m+n days before the (N+1)-thday to the time that is m days before the (N+1)-th day. When theevaluation is performed at an (N+2)-th day, a unit space A(N+2) iscreated based on the quantity of state of the gas turbine powergeneration plant 1 acquired for n days from the time that is m+n daysbefore the (N+2)-th day to the time that is m days before the (N+2)-thday.

When the N-th day is a reference point and the evaluation is performedat the (N+1)-th day, the unit space A(N+1) is created based on thequantity of state of the gas turbine power generation plant 1 acquiredfor n days from the time that is (m+n−1) days before the N-th day to thetime that is m days before the (N+1)-th day. When the evaluation isperformed at an (N+2)-th day, the unit space A(N+2) is created based onthe quantity of state of the gas turbine power generation plant 1acquired for n days from the time that is (m+n−2) days before the N-thday to the time that is m days before the (N+2)-th day.

In this embodiment, the unit space is created based on the quantity ofstate acquired during a predetermined period (in this embodiment, ndays) before evaluation. In the creation of the unit space, new quantityof state is acquired as data every day over time. In addition, when atime corresponding to the evaluation has elapsed, the past quantity ofstate is sequentially removed from the creation of the unit space. Asdescribed above, when the evaluation is performed at the N-th day, theunit space A(N) is created based on the quantity of state of the gasturbine power generation plant 1 acquired for n days from the time thatis m days before the evaluation to the time that is n days before thatday. When the evaluation is performed at the (N+1)-th day after one fullday (24 hours) has elapsed from the N-th day, the unit space A(N+1) iscreated based on the quantity of state of the gas turbine powergeneration plant 1 acquired for n days from the time that is m−1 daysbefore the N-th day to the time that is n days before that day. That is,when the evaluation time is changed from the N-th day to the (N+1)-thday, the quantity of state that has not been collected at the N-th daywhere the evaluation is performed, that is, the quantity of statecollected for one day from the time that is m−1 days before the N-th dayto the time that is one day before that time is used to create the unitspace A(N+1). In addition, the quantity of state that has been collectedat the N-th day where the evaluation is performed, that is, the quantityof state collected for one day from the time that is (m+n−1) days beforethe N-th day to the time that is one day before that time is removedfrom the creation of the unit space A(N+1).

As such, in this embodiment, the period for which the state value (thequantity of state for creating a unit space) used to create the unitspace is acquired is moved with the progress of evaluation, and new unitspace is created whenever the state of the gas turbine power generationplant 1 is evaluated. As such, the period for which information used tocreate the unit space is acquired is moved with the progress ofevaluation. Therefore, even when the quantity of state is changed due toa variation in the state of parts, such as abrasion, over time inaddition to a season variation, it is possible to create the unit spacein consideration of the influence of the variation. As a result, evenwhen the quantity of state is changed due to allowed and assumedfactors, such as a variation in performance over time, in addition tothe season variation, it is possible to prevent a reduction in theaccuracy of the determination of the state of the gas turbine powergeneration plant 1 and accurately determine whether the state of the gasturbine power generation plant 1 is normal or abnormal.

In the above Patent Citation 1, a plurality of unit spaces is preparedfor each season. However, for example, when abnormal weather conditions,such as cold summer and warm winter, occur, it is difficult to reflectthe influence of the abnormal weather conditions to the unit space. As aresult, in the technique disclosed in the above Patent Citation 1, theaccuracy of the determination of the state of the gas turbine powergeneration plant 1 is lowered, and a normal state is likely to bedetermined to be an abnormal state. In this embodiment, since the periodfor which information used to create the unit space is moved with theprogress of evaluation, it is possible to reflect the influence of, forexample, the abnormal weather conditions to the unit space. As a result,it is possible to prevent a reduction in the accuracy of thedetermination of the state of the gas turbine power generation plant 1and accurately determine whether the state of the gas turbine powergeneration plant 1 is normal or abnormal.

In addition, in the above Patent Citation 1, it is necessary to preparea plurality of unit spaces for each season. However, in this embodiment,since the period for which the quantity of state (the quantity of statefor creating a unit space) used to create the unit space is moved withthe progress of evaluation, it is not necessary to prepare a pluralityof unit spaces. Therefore, it is possible to reduce the storage area ofthe unit space in the storage unit 13 provided in the plant statemonitoring apparatus 10. As a result, it is possible to effectively usethe hardware resources of the plant state monitoring apparatus 10. Inthis embodiment, since a new unit space is created whenever the gasturbine power generation plant 1 is evaluated, it is possible to createa unit space for each plant. As a result, it is possible to evaluate thestate of each plant in consideration of the characteristics of theplant, which results in an increase in the accuracy of evaluation.

It is preferable that information acquired at any time of one day beused as the quantity of state, which is the quantity of state forcreating a unit space use. In this case, only one state quantity or mstate quantities are used as information for creating a unit time.Therefore, it is possible to reduce the amount of information forcreating a unit time. In this way, it is possible to reduce theoperation load of the processing unit 12 provided in the plant statemonitoring apparatus 10 and the storage area of the information forcreating a unit time in the storage unit 13. As a result, it is possibleto effectively use the hardware resources of the plant state monitoringapparatus 10. It is preferable that n be at least 30 days and at most 80days. In this embodiment, n is 60 days. In addition, it is preferablethat m be at least 3 days and at most 10 days. In this embodiment, m is10 days. Information at a plurality of times of one day may be used asthe quantity of state, which is the quantity of state for creating aunit space.

In this embodiment, the period for which the quantity of state (thequantity of state for creating a unit space) used to create the unitspace is moved with the progress of evaluation. When the quantity ofstate of the gas turbine power generation plant 1 is gradually changedto an abnormal state and the evaluation operation is included in theperiod, the creation of the unit space is affected by an abnormal statequantity. As a result, the accuracy of the determination of the state ofthe gas turbine power generation plant 1 is likely to be reduced. Inthis embodiment, the state value acquired during a predetermined periodbefore the evaluation (in this embodiment, for m days before theevaluation) is not used to create the unit time. In this way, thecreation of the unit space is less affected by an abnormal statequantity. Therefore, the accuracy of the determination of the state ofthe gas turbine power generation plant 1 is less likely to be reduced.As a result, even though abnormality in the quantity of state of the gasturbine power generation plant 1 gradually appears, it is possible todetect the abnormality.

When the quantity of state for creating a unit space is acquired by theabove-mentioned method, the process proceeds to Step S203. In Step S203,the unit space creating unit 12 a calculates a unit space from thequantity of state for creating a unit space acquired in Step S202. Inthis embodiment, the number of quantities of state is L, and the unitspace is an L-dimensional space. Then, the process proceeds to StepS204, and the Mahalanobis distance calculating unit 12 b of the plantstate monitoring apparatus 10 calculates the Mahalanobis distance Dduring evaluation.

The Mahalanobis distance D is calculated by Expression 5. In this case,the inverse matrix R⁻¹ of the covariance matrix R in Expression 5 iscalculated from data (the quantity of state) of the unit spacecalculated in Step S203. That is, the Mahalanobis distance D iscalculated based on the unit space. In Expression 5, x_(kj) is obtainedby converting a variable X_(kj) allocated to the quantity of state ofthe gas turbine power generation plant 1 acquired during evaluation intothe random variable of the standard deviation 1 using Expression 3.Here, k indicates the number (u) of quantities of state, and j indicatesthe number of quantities of state of the gas turbine power generationplant 1 acquired during evaluation.

Then, the process proceeds to Step S205 and the threshold value Dc isset. In this case, the order of Step S204 and Step S205 may be changed.As described above, the Mahalanobis distance D is increased as thedistance from the unit space is increased, that is, according to thedegree of abnormality. The Mahalanobis distance D is substantially atmost 4 when reference data, that is, the average value of the unit spaceis 1 and the quantity of state of the gas turbine power generation plant1 is a normal state. Therefore, for example, the threshold value Dc maybe appropriately set to a value that is more than the maximum value ofthe unit space. In addition, the threshold value Dc may be set inconsideration of inherent characteristics of the gas turbine powergeneration plant 1 or a variation in the manufacture of the gas turbinepower generation plant 1. The threshold value Dc may be a predeterminedvalue.

FIG. 4 is a diagram illustrating the unit space A created using theoutput P of the power generator 5 and the temperature θ of the air drawninto the compressor 2 as the quantity of state for creating a unitspace. In FIG. 4, B indicates the quantity of state, that is, themeasured values of the output P of the power generator 5 and thetemperature θ of the air drawn into the compressor 2. A solid lineindicating the unit space A indicates the threshold value Dc. Inaddition, D indicates the Mahalanobis distance. When the quantity ofstate (in FIG. 4, the output P and the temperature θ of the air drawn)during evaluation is within the threshold value Dc (G in FIG. 4), it canbe determined that the gas turbine power generation plant 1 is in anormal state. When the quantity of state during evaluation is more thanthe threshold value Dc (E and F in FIG. 4), it can be determined thatthe gas turbine power generation plant 1 is in an abnormal state. InFIG. 5, since D<Dc is satisfied up to a time T=T6, it is determined thatthe gas turbine power generation plant 1 is in a normal state. However,since D>Dc is satisfied at a time T=T7, it is determined that the gasturbine power generation plant 1 is in an abnormal state.

In Step S206, the plant state determining unit 12 c of the plant statemonitoring apparatus 10 compares the Mahalanobis distance D acquired inStep S204 with the threshold value Dc set in Step S205. When thedetermination result in Step S206 is “Yes”, that is, when the plantstate determining unit 12 c determines that the Mahalanobis distance Dis at most the threshold value Dc, it is determined that the gas turbinepower generation plant 1 is in a normal state (Step S207). In this case,the plant state monitoring method according to this embodiment isconcluded.

When the determination result in Step S206 is “No”, that is, when theplant state determining unit 12 c determines that the Mahalanobisdistance D is more than the threshold value Dc, it is determined thatthe gas turbine power generation plant 1 is in an abnormal state (StepS208). In this case, the process proceeds to Step S209, and the plantstate determining unit 12 c displays the Mahalanobis distance D that hasbeen determined to be abnormal on the display 14D of the control panel14. The displayed Mahalanobis distance D is calculated in Step S204.Then, the process proceeds to Step S210, and the plant state determiningunit 12 c estimates the items of abnormal state quantities from thedifference between the larger-the-better SN (Signal/Noise) ratiosaccording to whether there are items by, for example, orthogonal tableanalysis. Whether there is an abnormality can be determined from theMahalanobis distance D. However, it is difficult to determine a placewhere abnormality occurs from the Mahalanobis distance D. It is easy tospecify the place where abnormality occurs or clear up the cause of theabnormality by estimating the items of abnormal state quantities. Theplant state determining unit 12 c displays the estimated abnormal statequantities on the display 14D of the control panel 14. The differencebetween the larger-the-better SN ratios according to whether there areitems by the orthogonal table analysis is increased in the quantity ofstate of the abnormal item. Therefore, it is possible to specifyabnormal factors by checking the items with a large difference betweenthe larger-the-better SN ratios, for example, the top three items.

According to the above-described embodiment, the unit space used tocalculate the Mahalanobis distance or determine whether the plant is ina normal state or an abnormal state is created based on the quantity ofstate of the plant acquired during the period from the time that is apredetermined time before the time when the state of the plant isevaluated to the time that is a predetermined time before that time. Inthis way, the period for which information used to create the unit spaceis acquired is moved with the progress of evaluation. Therefore, evenwhen the quantity of state is changed due to an allowed and assumedfactor, for example, a variation with time, in addition to a seasonvariation, it is possible to create the unit space in consideration ofthe influence of the variation with time. As a result, it is possible toreflect factors causing a variation in the quantity of state to the unitspace. In this way, it is possible to prevent the accuracy of thedetermination of the state of a gas turbine power generation plant frombeing reduced and accurately determine whether the gas turbine powergeneration plant is in a normal state or an abnormal state.

INDUSTRIAL APPLICABILITY

The plant state monitoring method, the plant state monitoring computerprogram, and the plant state monitoring apparatus according to theinvention are effective in monitoring the state of a plant anddetermining whether the state of the plant is normal or abnormal. Inparticular, according to the invention, it is possible to accuratelydetermine whether a plant is in a normal state or an abnormal state.

1. A plant state monitoring method of monitoring an operation state of aplant using a Mahalanobis distance related to state quantities of theplant, comprising: acquiring state quantities of the plant used tocreate a third unit space from the plant, the third unit space being afirst set of data regarding various kinds of state quantities, andserving as standard for determining whether or not the operation stateof the plant is normal; acquiring a second set of data regarding thevarious kinds of the state quantities of the plant when the state of theplant is evaluated; calculating a Mahalanobis distance of the second setof data regarding the various kinds of the state quantities acquiredwhen the state of the plant is evaluated, based on the third unit space;and determining the state of the plant based on the calculatedMahalanobis distance and a predetermined threshold value, wherein thethird unit space is created based on the state quantities of the plantduring a period from the time that is a fifth time before the time whenthe state of the plant is evaluated to the time that is a sixth timebefore that time.
 2. The plant state monitoring method according toclaim 2, wherein a period for which the state quantities of the plantused to create the third unit space are acquired is shifted along withprogress of evaluating the state of the plant, and thereby a new unitspace is created whenever the plant is evaluated.
 3. The plant statemonitoring method according to claim 1, wherein the state quantities ofthe plant, during a period from the time that is a fifth time before thetime when the state of the plant is evaluated to the time that is asixth time before that time, are used to create the unit space, and thestate quantities of the plant, at any time or a plurality of times inone solid day within the period for which the state quantities arecollected, are used to create the unit space.
 4. The plant statemonitoring method according to claim 1, wherein the state quantitiesused to create the unit space are excluded in chronological order fromthe creation of the third unit space, such that the oldest one isexcluded first.
 5. A plant state monitoring computer program embodied ina tangible medium, executed to cause a computer of a plant statemonitoring apparatus, which monitors an operation state of a plant usinga Mahalanobis distance related to state quantities of the plant, toperform a plant state monitoring method comprising: acquiring statequantities of the plant used to create a third unit space from theplant, the third unit space being a first set of data regarding variouskinds of state quantities, and serving as a standard for determiningwhether or not the operation state of the plant is normal; acquiring asecond set of data regarding the various kinds of the state quantitiesof the plant when the state of the plant is evaluated; calculating aMahalanobis distance which is the set of data regarding the variouskinds of the state quantities acquired when the state of the plant isevaluated, based on the third unit space; and determining the state ofthe plant based on the calculated Mahalanobis distance and apredetermined threshold value, wherein the third unit space is createdbased on the state quantities of the plant during a period from the timethat is a fifth time before the time when the state of the plant isevaluated to the time that is a sixth time before that time.
 6. Theplant state monitoring computer program according to claim 5, wherein aperiod for which the state quantities of the plant used to create thethird unit space are acquired is shifted along with progress ofevaluating the state of the plant, and thereby a new unit space iscreated whenever the plant is evaluated.
 7. A plant state monitoringapparatus for monitoring an operation state of a plant, comprising: aunit space creating unit which creates a third unit space based on avarious kinds of the state quantities of the plant during a period fromthe time that is a fifth time before the time when the state of theplant is evaluated to the time that is a sixth time before that time,the third unit space being a first set of data regarding the variouskinds of the state quantities, and serving as a standard for determiningwhether or not the state of the plant is normal; a Mahalanobis distancecalculating unit which calculates a Mahalanobis distance of a second setof data regarding the various kinds of the state quantities acquiredwhen the state of the plant is evaluated, based on the third unit space;and a plant state determining unit which determines the state of theplant based on the Mahalanobis distance calculated by the Mahalanobisdistance calculating unit and a predetermined threshold value obtainedfrom the third unit space created by the unit space creating unit. 8.The plant state monitoring apparatus according to claim 7, wherein aperiod for which the state quantities of the plant used to create thethird unit space are acquired is shifted along with progress ofevaluating the state of the plant, and thereby a new unit space iscreated whenever the plant is evaluated.
 9. The plant state monitoringapparatus according to claim 7, wherein the state quantities of theplant, during a period from the time that is a fifth time before thetime when the state of the plant is evaluated to the time that is asixth time before that time, are used to create the unit space, and thestate quantities of the plant, at any time or a plurality of times inone solid day within the period for which the state quantities arecollected, are used to create the unit space.
 10. The plant statemonitoring apparatus according to claim 7, wherein the state quantitiesused to create the unit space are excluded in chronological order fromthe creation of the third unit space, such that the oldest one isexcluded first.